Humanitarian Robotics and the Threat of a Jobless Future

Martin Ford’s Rise of the Robots: Technology and the Treat of a Jobless Future is one of the best books I read in 2015. It is a New York Times Bestseller and was selected as the Top Business Book of 2015 by Forbes. “We are, in all likelihood, at the leading edge of an explosive wave of innovation,” writes Ford. This wave will “ultimately produce robots geared toward nearly every conceivable commer-cial, industrial and consumer task.” Some of these robots may prove invaluable in supporting humanitarian efforts. Indeed, some already have. Saving lives and alleviating suffering during disasters is typically considered a plus. Robotics solutions can scale these efforts. The catch lies in the last two words of the book’s title: Jobless Future.

The robotics solutions that are starting to have an impact in the humanitarian space are largely “first generation” robotics platforms. The real explosion and impact will be felt during the second wave when these systems become more intelligent, autonomous and persistent. This may radically improve the efficiency and productivity of humanitarian efforts, thereby alleviating more suffering and potentially saving more lives. The tradeoff, however, may be staggering levels of unemployment. According to Ford, “nearly half of US total employment may be vulnerable to automation within roughly the next two decades.” Could this also become true for those employed by aid organizations?

If so, some humanitarian professionals will be particularly pleased. I’ve often heard this notion that humanitarians should seek to work themselves out of a job. If we do our job well, the thinking goes, then we should be able to work ourselves out of a job. If we build local capacity, for example, and empower our local counterparts to take over, then our job will be done as we will no longer be needed. Of course, reality is somewhat more complicated.

Lets game this out using a few scenarios. Take flying robots like “UAVs” or “drones”, for example. Aerial robots can collect data (e.g., take photographs) of disaster affected areas and carry payloads (e.g., essential medicines) from clinics to villages. Take the second use-case, payload delivery. I’ve been exploring this use-case for a number of projects in Nepal and the Philippines. It currently takes 7 hours to transport medicines between a hospital and a remote, mountain village in Nepal’s Myagdi District. The reason it takes this long is because of the very mountainous terrain which in turn means there are no roads connecting said village. As a result, the medicines need to be transported by foot. The aerial distance between these two points is only 5 miles, however, a distance that could be covered in about 20 minutes by a flying drone. In sum, the robot would be 400 minutes faster.

Now what happens to the local Napali carriers who were employed to walk the 7 hours to deliver those essential medicines? They’re out of work. Could they be retrained and hired to operate, maintain or recover UAVs that deliver the medicines? Yes, possibly. Three international companies I’ve spoken to are planning to follow this strategy. But does operating an intelligent, autonomous system really require 10 ex-carriers? Unlikely. A company might just hire two ex-carriers to operate the system, switch the batteries, change payloads, etc. Any other carriers, however, are now unemployed. That said, since the UAV is being used to service this one remote village, the same UAV could be used to serve other “nearby” villages that do not have access to medicines. No carriers serve these locations. As such, the carriers who were rendered obsolete due to the first UAV route, may potentially have new jobs after all by helping the company expand their service through new UAV routes.

In any event, there is not much upwards mobility for traditional carriers, regardless of whether they deliver by foot or use motorbikes. Such jobs are not dream jobs; they are laborious and physically challenging. In contrast, receiving basic training on how to operate UAVs offers these carriers transferable skills that can enable them to get better jobs in more technical industries.

But what if they don’t regain employment? Does the positive social impact that results from more frequent and reliable delivery of essential medicines via aerial robotics solutions outweigh the negative social impact of local job losses? I suppose it depends on which theory of normative ethics you subscribe to. In any event, this is all quite speculative; there more variables that need to be factored into the above narrative; highly local, seasonal and context specific variables. I could certainly see the scenario in Nepal playing out in many different ways, both positively and negatively.

What about the use of robotics for data collection? Perhaps this one is more straightforward. The comparative analysis here is typically with satellites (space robotics) and manned aircraft. UAVs can collect certain data that satellites and manned aircraft are unable to. This may explain why industry statistics confirm that the commercial UAV space is creating new jobs rather than taking them away from the space & aviation industries. Since our Nepali carriers above are already trained in operating UAVs for payload delivery, they would already have most of the core skills needed to operate UAVs for data collection purposes. And as it turns out, there is growing local demand for such services in Nepal.

In any event, robotics companies should carry out impact assessments vis-a-vis local employment opportunities—particularly for projects that focus on payload delivery systems. A percentage of the profit made by that provide more efficient aerial delivery services should be used to retrain those rendered obsolete by the introduction of robotics solutions, particularly for projects in low income districts. Martin Ford doesn’t buy the policy around retraining, however. In fact, he basically demolishes the entire economic argument with rather compelling historical evidence. Instead, he recommends the use of guaranteed minimum incomes or “citizen’s dividends” as one remedy to cushion the impact of a jobless future. So perhaps a percentage of profits that accrue to international robotics companies could be redistributed to support local, primarily low-skilled laborers who are rendered unemployed by the introduction of robotics solutions and related services. Wishful thinking?

Regardless of which policy solutions end up being implemented and what for-profit companies decide to do, what is certain the extended time it will until political institutions decide which to pursue, how and when. In the meatime, the Fourth Industrial Revolution may drive the greatest “digital divide” yet between the have’s and have nots. To be sure, the commercial and consumer robotics industry is expected to become a much bigger multi-billion industry in coming years. But the growing “robotics divide” means that those who profit from this revolution are unlikely to be local companies in developing countries. The largest manufacturers of aerial robotics companies, for example, are Chinese, European and American. The same is largely true of robotics service companies.

But developing countries can still participate in the Fourth Industrial Revolution by catching up on the service side. That is, demand for robotics-as-a-service is expected to skyrocket in both developing and emerging economies. We thus need to transfer the necessary skills and relevant robotics technologies to hard-working local partners and support their efforts to incubate local start-ups that offer a range of robotics services. These local start-ups will have important comparative advantages over Western companies seeking to provide similar services. They’ll already be on-site with the technology; they’ll know the language and understand the local market better. They’ll have a better grasp of context-specific use-cases and hence local business intelligence. What’s more, they’ll be able to offer more rapid services at more competitive prices than competing companies based in the West.

This is one of the main motivations behind Flying Labs. We want to actively reduce the inequality caused by the Fourth Industrial Revolution. Our plan is to build a global network of Flying Labs and thereby create a local, highly-skilled technology workforce that can take advantage of the rising demand in robotics services. Members of our Flying Labs will first apply their skills and robotics technologies to support humanitarian, development and environmental efforts. As they gain experience, expertise and visibility in the social good sector, they will market their services to other sectors and industries that exhibit growing signs of demand inside their countries. Given that the Flying Labs will already be local, they would also have a first-mover advantage in catering to local demand.

In sum, we hope that Flying Labs will create local tech jobs that reduce the “robotics divide” by spinning off successful robotics service companies. These local start-ups could provide guaranteed minimum incomes (“citizen dividends”) and new training opportunities for those low-skilled workers displaced by the new robotics solutions. A local start-up incubated by a local social innovation lab focused on building local capacity building and social good may embrace this social responsibility more readily than an international company from Silicon Valley with no cultural or historical ties to the country in question.

I’d be grateful for feedback on the above arguments and assumptions. Is the logic sound? What am I overlooking? Am I wrong? What else should I be considering?

Updates:

“About half the human labor in warehouses slogs away on simple, arduous tasks that involve moving stuff around—doing work that’s the equivalent of restocking shelves in a grocery store. It’s strenuous work, with employees often walking more than a dozen miles a day as part of their job. As new robots become available, particularly to e-commerce warehouses with vast inventories and complex packing operations, these are the people whose jobs will be most at risk” (Bloomberg, June 2016).

“AI can seem dystopian because it’s easier to describe existing jobs disappearing than to imagine industries that never existed appearing.” – Aaron Levie, July 2016.